Calculating vif_scores resulting in error because X_AS_train.values is an array of object

[jiratpasuksmit]

Error at def AutoSpearman line 101

variance_inflation_factor must be called nparray of any type that is not object. However, the lib send nparray of object (X_AS_train.values). I'm not sure why and whether it is only happened on my case. :(

I fix on my local as in diff and it runs fine.

OB: call pyExplainer = pyexplainer_pyexplainer.PyExplainer(X_train=trainFeatureDf, y_train=trainY, indep=trainFeatureDf.columns, dep=field.LABEL, blackbox_model=model, class_label=[False, True]) pyExplainer.auto_spearman()

Return Stacktraces:

Traceback (most recent call last): File "/Applications/PyCharm.app/Contents/plugins/python/helpers/pydev/pydevd.py", line 1483, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "/Applications/PyCharm.app/Contents/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "/Users/jpasuksmit/agile-requirement/model/TestPyExplainer.py", line 48, in pyExplainer.auto_spearman() File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/pyexplainer/pyexplainer_pyexplainer.py", line 444, in auto_spearman X_AS_train = AutoSpearman(self.X_train, correlation_threshold, correlation_method, VIF_threshold) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/pyexplainer/pyexplainer_pyexplainer.py", line 101, in AutoSpearman vif_scores = pd.DataFrame([variance_inflation_factor(np.array(X_AS_train.values, dtype=float), i) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/pyexplainer/pyexplainer_pyexplainer.py", line 101, in vif_scores = pd.DataFrame([variance_inflation_factor(np.array(X_AS_train.values, dtype=float), i) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/stats/outliers_influence.py", line 192, in variance_inflation_factor r_squared_i = OLS(x_i, x_noti).fit().rsquared File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/regression/linear_model.py", line 872, in init super(OLS, self).init(endog, exog, missing=missing, File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/regression/linear_model.py", line 703, in init super(WLS, self).init(endog, exog, missing=missing, File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/regression/linear_model.py", line 190, in init super(RegressionModel, self).init(endog, exog, kwargs) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/model.py", line 237, in init super(LikelihoodModel, self).init(endog, exog, kwargs) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/model.py", line 77, in init self.data = self._handle_data(endog, exog, missing, hasconst, File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/model.py", line 101, in _handle_data data = handle_data(endog, exog, missing, hasconst, **kwargs) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/data.py", line 672, in handle_data return klass(endog, exog=exog, missing=missing, hasconst=hasconst, File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/data.py", line 87, in init self._handle_constant(hasconst) File "/Users/jpasuksmit/anaconda3/envs/agile-requirement/lib/python3.8/site-packages/statsmodels/base/data.py", line 132, in _handle_constant if not np.isfinite(exog_max).all(): TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''